Tuscany
Mukim Kuala Lumpur, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
Mukim Kuala Lumpur, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
New Condo in PJ Damansara
Pet friendly condo. 10mins to 1Utama
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Nearby areas in Mukim Kuala Lumpur
M Vertica
Residensi Laman Permai (Goodwood)
Taman Tun Dr Ismail
Damansara Heights (Bkt Damansara)
The Scott Garden
South Link Bangsar South
Taman Midah
Pantai Hillpark Apartment
Sri Penara
Bangsar Baru
Taman Desa
The Vyne
Tuscany
PSF median price per sq ft · 12m its change over the past 12 months
Most-traded areas in this mukim, by number of recorded subsale transactions. See every area in Mukim Kuala Lumpur
New Condo in PJ Damansara
Pet friendly condo. 10mins to 1Utama
New Condo in PJ Damansara
From RM600,000 · 800 sqft
Pet friendly condo. 10mins to 1Utama
Mukim Kuala Lumpur, Kuala Lumpur, Federal Territory of Kuala Lumpur, Malaysia
MapsTuscany in Kuala Lumpur, Kuala Lumpur recorded 0 subsale transactions in 2021, with a median price of RM760K and a median price per square foot (PSF) of RM751.
This area consists exclusively of residential properties, with no commercial listings recorded.
Price remained flat, and PSF growth was PSF remained flat. The median price is RM760K, with most transactions falling within a stable range of RM570K to RM950K, and a typical market range of RM665K to RM855K.
Most transactions involved condominium/apartment, with minimal variety in property types.
For price per square foot, the median is RM751, with most transactions between RM735 and RM767. The usual range is RM743.00 to RM759.00, showing that most units are priced quite close to each other. A typical spread (IQR) of RM16.00 and an average deviation (MAD) of RM16 indicate a highly stable PSF trend across properties.
Overall, the market in this area appears stable with consistent appreciation, making it an attractive option for both investors and homebuyers. Moderate price stability provides a balanced market for both buyers and sellers. Limited transaction history suggests carefully evaluating comparable sales data.